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DBMS > Databricks vs. Google Cloud Firestore vs. Sphinx vs. Tkrzw

System Properties Comparison Databricks vs. Google Cloud Firestore vs. Sphinx vs. Tkrzw

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonSphinx  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Open source search engine for searching in data from different sources, e.g. relational databasesA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument store
Relational DBMS
Document storeSearch engineKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.databricks.comfirebase.google.com/­products/­firestoresphinxsearch.comdbmx.net/­tkrzw
Technical documentationdocs.databricks.comfirebase.google.com/­docs/­firestoresphinxsearch.com/­docs
DeveloperDatabricksGoogleSphinx Technologies Inc.Mikio Hirabayashi
Initial release2013201720012020
Current release3.5.1, February 20230.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemshostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnono
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnono
Secondary indexesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query language (SphinxQL)no
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Proprietary protocol
Supported programming languagesPython
R
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes, Firebase Rules & Cloud Functionsnono
Triggersyes, with Cloud Functionsnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.nono
More information provided by the system vendor
DatabricksGoogle Cloud FirestoreSphinxTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGoogle Cloud FirestoreSphinxTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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